ArchitectureA supervised JVM-class runtime — OLTP on seven engines, OLAP on three. AI-native, MCP-native, observable as plain SQL.Read the architecture
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Cohere embeddings and tokenizer, multimodal Vertex embeddings, a price per model

Cohere's embedding models join through its second-generation API with retries, and its tokenizer is reachable from scripts. Vertex AI embeds text, image, audio, video and documents. Every provider model carries a price.

Retrieval quality depends on the embedding model, and cost depends on knowing what each call costs. This release adds a provider on one side and a price on the other.

Cohere

  • Embeddings The four third-generation embedding models on the second-generation API, with retry, parallelism and a configurable input type.
  • Tokenizer Encode, decode and estimate through the tokenize and detokenize endpoints, exposed to scripts, with credentials as a plain key, an encrypted field or a third-party credential.

Vertex and pricing

  • Multimodal embeddings Structured requests for text, image, audio, video and documents with task-specific parameters and usage tracking, on the global endpoint, with the deprecated models replaced.
  • A price per model Request and response pricing fields per provider model, and a service that answers what a model costs. Builder factories for chat, embedding, rerank and speech models are now global.

The spend quota of December 2024 needed a price to count. This is where the price comes from.